The size and extent of the Internet's projected use in the years ahead will require that successful e-businesses offer massively scalable solutions to problems such as how to personalize information for individual users. As Internet users become increasingly savvy and require more specialized information services, the complexity of developing both scalable and granular personalization solutions becomes compounded. Unfortunately, current access control technology lacks sufficiently scalable and finely granular personalization solutions.
The future of e-business will require ways to personalize information based upon a user's needs or preferences. Current storage mechanisms are inefficient in gathering and storing such a huge amount of data related to individuals. The market for a solution that addresses problems of customer relationship management in this regard is estimated to grow to $11 billion by 2002. Projections may increase even further if new applications for efficiently stored and categorized user preference information are developed.
The growth in popularity of wireless devices with limited user interfaces will sharpen the need for focused, targeted content, according to quick evaluation of users' preferences.
Information relating to a Web user's activity can be applied to all types of customer relationship models. As new presences on the Web start (and fail) daily, the obvious question remains of how an e-business can focus on those users that make their way through their electronic front door, recognizing its customers and storing information useful with respect to that customer's past activity in visits past. What is needed is a way to efficiently store and retrieve user preferences.
Certain types of individuals can be placed in characteristic groupings. However these groupings are gathered, their use adds considerable value to not only an e-business' knowledge of its customers, but to outsiders like prospective advertisers for which such categorizations often affect decisions on ad revenue placement. So long as there is a means to gather this information, there will be those that profit from its use. What is needed is a way to categorize user preferences into groups.
In addition to indicating the whether a given user prefers an object, there is also the need to identify the full set of objects preferred by an individual.